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Original author | Ana Huamán |
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Compatibility | OpenCV >= 3.0 |
Goals
In this tutorial you will learn how to
- Use the OpenCV function cv::findContours
- Use the OpenCV function cv::drawContours
Code
C++
The tutorial code is shown below. You can also download it from here
#include "opencv2/imgcodecs.hpp" #include "opencv2/highgui.hpp" #include "opencv2/imgproc.hpp" #include <iostream> using namespace cv; using namespace std; Mat src_gray; int thresh = 100; RNG rng(12345); void thresh_callback(int, void* ); int main(int argc, char** argv) {<!-- --> CommandLineParser parser( argc, argv, "{@input | HappyFish.jpg | input image}" ); Mat src = imread( samples::findFile( parser.get<String>( "@input" ) ) ); if( src.empty() ) {<!-- --> cout << "Could not open or find the image!\ " << endl; cout << "Usage: " << argv[0] << " <Input image>" << endl; return -1; } cvtColor( src, src_gray, COLOR_BGR2GRAY ); blur( src_gray, src_gray, Size(3,3) ); const char* source_window = "Source"; namedWindow( source_window ); imshow( source_window, src ); const int max_thresh = 255; createTrackbar( "Canny thresh:", source_window, & amp;thresh, max_thresh, thresh_callback ); thresh_callback(0, 0); waitKey(); return 0; } void thresh_callback(int, void* ) {<!-- --> Mat canny_output; Canny(src_gray, canny_output, thresh, thresh*2); vector<vector<Point> > contours; vector<Vec4i> hierarchy; findContours( canny_output, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE ); Mat drawing = Mat::zeros( canny_output.size(), CV_8UC3 ); for( size_t i = 0; i< contours.size(); i + + ) {<!-- --> Scalar color = Scalar( rng.uniform(0, 256), rng.uniform(0,256), rng.uniform(0,256) ); drawContours( drawing, contours, (int)i, color, 2, LINE_8, hierarchy, 0 ); } imshow( "Contours", drawing ); }
Java
The tutorial code is shown below. You can also download it from here
import java.awt.BorderLayout; import java.awt.Container; import java.awt.Image; import java.util.ArrayList; import java.util.List; import java.util.Random; import javax.swing.BoxLayout; import javax.swing.ImageIcon; import javax.swing.JFrame; import javax.swing.JLabel; import javax.swing.JPanel; import javax.swing.JSlider; import javax.swing.event.ChangeEvent; import javax.swing.event.ChangeListener; import org.opencv.core.Core; import org.opencv.core.CvType; import org.opencv.core.Mat; import org.opencv.core.MatOfPoint; import org.opencv.core.Point; import org.opencv.core.Scalar; import org.opencv.core.Size; import org.opencv.highgui.HighGui; import org.opencv.imgcodecs.Imgcodecs; import org.opencv.imgproc.Imgproc; class FindContours {<!-- --> private Mat srcGray = new Mat(); private JFrame frame; private JLabel imgSrcLabel; private JLabel imgContoursLabel; private static final int MAX_THRESHOLD = 255; private int threshold = 100; private Random rng = new Random(12345); public FindContours(String[] args) {<!-- --> String filename = args.length > 0 ? args[0] : "../data/HappyFish.jpg"; Mat src = Imgcodecs.imread(filename); if (src.empty()) {<!-- --> System.err.println("Cannot read image: " + filename); System.exit(0); } Imgproc.cvtColor(src, srcGray, Imgproc.COLOR_BGR2GRAY); Imgproc.blur(srcGray, srcGray, new Size(3, 3)); // Create and set up the window. frame = new JFrame("Finding contours in your image demo"); frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE); // Set up the content pane. Image img = HighGui.toBufferedImage(src); addComponentsToPane(frame.getContentPane(), img); // Use the content pane's default border layout. No need // setLayout(new BorderLayout()); //Show the window. frame.pack(); frame.setVisible(true); update(); } private void addComponentsToPane(Container pane, Image img) {<!-- --> if (!(pane.getLayout() instanceof BorderLayout)) {<!-- --> pane.add(new JLabel("Container doesn't use BorderLayout!")); return; } JPanel sliderPanel = new JPanel(); sliderPanel.setLayout(new BoxLayout(sliderPanel, BoxLayout.PAGE_AXIS)); sliderPanel.add(new JLabel("Canny threshold: ")); JSlider slider = new JSlider(0, MAX_THRESHOLD, threshold); slider.setMajorTickSpacing(20); slider.setMinorTickSpacing(10); slider.setPaintTicks(true); slider.setPaintLabels(true); slider.addChangeListener(new ChangeListener() {<!-- --> @Override public void stateChanged(ChangeEvent e) {<!-- --> JSlider source = (JSlider) e.getSource(); threshold = source.getValue(); update(); } }); sliderPanel.add(slider); pane.add(sliderPanel, BorderLayout.PAGE_START); JPanel imgPanel = new JPanel(); imgSrcLabel = new JLabel(new ImageIcon(img)); imgPanel.add(imgSrcLabel); Mat blackImg = Mat.zeros(srcGray.size(), CvType.CV_8U); imgContoursLabel = new JLabel(new ImageIcon(HighGui.toBufferedImage(blackImg))); imgPanel.add(imgContoursLabel); pane.add(imgPanel, BorderLayout.CENTER); } private void update() {<!-- --> Mat cannyOutput = new Mat(); Imgproc.Canny(srcGray, cannyOutput, threshold, threshold * 2); List<MatOfPoint> contours = new ArrayList<>(); Mat hierarchy = new Mat(); Imgproc.findContours(cannyOutput, contours, hierarchy, Imgproc.RETR_TREE, Imgproc.CHAIN_APPROX_SIMPLE); Mat drawing = Mat.zeros(cannyOutput.size(), CvType.CV_8UC3); for (int i = 0; i < contours.size(); i + + ) {<!-- --> Scalar color = new Scalar(rng.nextInt(256), rng.nextInt(256), rng.nextInt(256)); Imgproc.drawContours(drawing, contours, i, color, 2, Imgproc.LINE_8, hierarchy, 0, new Point()); } imgContoursLabel.setIcon(new ImageIcon(HighGui.toBufferedImage(drawing))); frame.repaint(); } } public class FindContoursDemo {<!-- --> public static void main(String[] args) {<!-- --> // Load the native OpenCV library System.loadLibrary(Core.NATIVE_LIBRARY_NAME); // Schedule a job for the event dispatch thread: // creating and showing this application's GUI. javax.swing.SwingUtilities.invokeLater(new Runnable() {<!-- --> @Override public void run() {<!-- --> new FindContours(args); } }); } }
Python
The tutorial code is shown below. You can also download it from here
from __future__ import print_function import cv2 as cv import numpy as np import argparse import random as rng rng.seed(12345) def thresh_callback(val): threshold = val # Use Canny to detect edges canny_output = cv.Canny(src_gray, threshold, threshold * 2) # Find contours contours, hierarchy = cv.findContours(canny_output, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE) # Draw contour lines drawing = np.zeros((canny_output.shape[0], canny_output.shape[1], 3), dtype=np.uint8) for i in range(len(contours)): color = (rng.randint(0,256), rng.randint(0,256), rng.randint(0,256)) cv.drawContours(drawing, contours, i, color, 2, cv.LINE_8, hierarchy, 0) # Display in window cv.imshow('Contours', drawing) #Load source image parser = argparse.ArgumentParser(description='Code for Finding contours in your image tutorial.') parser.add_argument('--input', help='Path to input image.', default='HappyFish.jpg') args = parser.parse_args() src = cv.imread(cv.samples.findFile(args.input)) if src is None: print('Could not open or find the image:', args.input) exit(0) # Convert image to gray and blur src_gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY) src_gray = cv.blur(src_gray, (3,3)) #Create window source_window = 'Source' cv.namedWindow(source_window) cv.imshow(source_window, src) max_thresh = 255 thresh = 100 # Initial threshold cv.createTrackbar('Canny Thresh:', source_window, thresh, max_thresh, thresh_callback) thresh_callback(thresh) cv.waitKey()
Results
The result is out